The issues addressed in this study include the relationship between efficiency and equity, the distributional effects of real world resource allocation constraints, and the resulting efficiency loss. The overall goal of this study is to develop a resource allocation model that can be used by a variety of policy makers to assess the consequences of different resource allocation decisions. To achieve the above goal, we will focus on the allocation of resources for the primary prevention of Coronary Heart Disease (CHD) in South Carolina. Services recommended, by the US Preventive Services Task Force for CHD risk factors (hypertension, hyperlipidemia, smoking, sedentary life style, diabetes, and menopause (hormone replacement therapy) will be studied. We will develop a resource allocation model that combines the demographics of South Carolina (county level age, gender and race) with current epidemiologic data (county specific CHD risk factor prevalence) and cost effectiveness data to calculate the most efficient (maximum life years gained) distribution of additional CHD prevention resources. The model will measure the effect of constraints (limited funding, proportional allocation of funding across gender and race, equal allocation of funding across counties, proportional allocation of funding across counties based prevalence of CHD risk factors, and proportional allocation of funding across preventive interventions) on efficiency (life years). In addition, the model will map the distribution of resources by county, intervention, age, gender and race. The model will utilize both linear programming and mixed integer programming in the identification of the most efficient allocation of additional CHD prevention resources. The algorithms will be set to maximize the potential life years gained as a result of the additional resources. The study will then compare the cost in life years that specific allocation constraints impose. In addition, we will compare the differences in resource allocation across intervention, county, age, gender and racial groups that result from the different constraints. Results of this study will be disseminated to both researchers and South Carolina policy makers.